Our Application in a Box (AnB) project, presented at SMARTCOMP 2023, simplifies the deployment of remote 5G applications. AnB includes pre-configured hardware and software, allowing quick setup without extensive technical knowledge. It features automated resource management for optimized performance, demonstrating real-world applications and significantly reducing deployment time from months to minutes.
At the PDP 2023 conference, we presented a study on application scaling in microservices deployed via Kubernetes. It critiques the Horizontal Pod Autoscaler (HPA) for inefficient scaling due to neglecting microservice interactions. The proposed DataX AutoScaler improves performance by accounting for these interactions, achieving up to 43% better performance in video analytics applications.
At the 9th International Conference on IOTSMS 2022, we presented a reinforcement-learning technique to enhance serverless edge computing by optimizing resource allocation for microservices. This innovative approach achieved remarkable improvements in processing rate in real-world applications, demonstrating versatility and efficiency that promise to revolutionize AI and machine learning.
In the 20th IEEE International Conference on Pervasive Intelligence and Computing (PICom 2022) A big challenge in changing a monolithic application into a performant microservices-based application is the design of efficient mechanisms for microservices to communicate with each other. Prior proposals range from custom point-to-point communication among microservices using protocols like gRPC to service meshes … Continue reading DataXc: Flexible and efficient communication in microservices-based stream analytics pipelines
In the 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) A key barrier to building performant, remotely managed and self-optimizing multi-sensor, distributed stream processing edge applications is high programming complexity. We recently proposed DataX [1], a novel platform that improves programmer productivity by enabling easy exchange, transformations, … Continue reading DataXe: A System for Application Self-optimization in Serverless Edge Computing Environments
The exponential growth in smart sensors and rapid progress in 5G networks is creating a world awash with data streams. However, a key barrier to building perfor- mant multi-sensor, distributed stream processing applications is high programming complexity. We propose DataX, a novel platform that improves programmer productivity by enabling easy exchange, transformations, and fusion of data streams. DataX abstraction simplifies the application’s specification and exposes parallelism and dependencies among the application functions (microservices). DataX runtime automatically sets up appropriate data communication mechanisms, enables effortless reuse of microservices and data streams across applications, and leverages serverless computing to transform, fuse, and auto-scale microservices. DataX makes it easy to write, deploy and reliably operate distributed applications at scale. Synthesizing these capabilities into a single platform is substantially more transformative than any available stream processing system.
Giuseppe Coviello 